Localized failure mode decorrelation in redundancy encoded data storage systems

ABSTRACT

A data storage system, such as an archival storage system, implements failure decorrelation methods. In some embodiments, a selector is employed to select one or more data storage devices of a host for storage of incoming data. In some of such embodiments, the selector selects from among the storage devices in a random, pseudorandom, stochastic, or deterministic fashion so as to prevent correlation of one or more failure modes associated with storage of the data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application incorporates by reference for all purposes the full disclosure of co-pending U.S. patent application Ser. No. 14/741,409, filed Jun. 16, 2015, entitled “ADAPTIVE DATA LOSS MITIGATION FOR REDUNDANCY CODING SYSTEMS,” U.S. patent application Ser. No. 14/789,778, filed Jul. 1, 2015, entitled “INCREMENTAL MEDIA SIZE EXTENSION FOR GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/789,783, filed Jul. 1, 2015, entitled “GRID ENCODED DATA STORAGE SYSTEMS FOR EFFICIENT DATA REPAIR,” U.S. patent application Ser. No. 14/789,789, filed Jul. 1, 2015, entitled “CROSS-DATACENTER EXTENSION OF GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/789,799, filed Jul. 1, 2015, entitled “CROSS-DATACENTER VALIDATION OF GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/789,810, filed Jul. 1, 2015, entitled “INCREMENTAL UPDATES OF GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/789,815, filed Jul. 1, 2015, entitled “NON-PARITY IN GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/789,825, filed Jul. 1, 2015, entitled “REBUNDLING GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/860,706, filed Sep. 21, 2015, entitled “EXPLOITING VARIABLE MEDIA SIZE IN GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/673,796, filed Mar. 30, 2015, entitled “FAILURE-DECOUPLED VOLUME-LEVEL REDUNDANCY CODING TECHNIQUES,” U.S. patent application Ser. No. 14/789,837, filed Jul. 1, 2015, entitled “DETERMINING DATA REDUNDANCY IN GRID ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/973,712, filed concurrently herewith, entitled “TECHNIQUES FOR COMBINING GRID-ENCODED DATA STORAGE SYSTEMS,” U.S. patent application Ser. No. 14/973,716, filed concurrently herewith, entitled “FLEXIBLE DATA STORAGE DEVICE MAPPING FOR DATA STORAGE SYSTEMS,” and U.S. patent application Ser. No. 14/973,708, filed concurrently herewith, entitled “TECHNIQUES FOR EXTENDING GRIDS IN DATA STORAGE SYSTEMS.”

BACKGROUND

The use of network computing and storage has proliferated in recent years. The resources for network computing and storage are often provided by computing resource providers who leverage large-scale networks of computers, servers and storage drives to enable clients, including content providers, online merchants and the like, to host and execute a variety of applications and web services. Content providers and online merchants, who traditionally used on-site servers and storage equipment to host their websites and store and stream content to their customers, often forego on-site hosting and storage and turn to using the resources of the computing resource providers. The usage of network computing allows content providers and online merchants, among others, to efficiently and to adaptively satisfy their computing needs, whereby the computing and storage resources used by the content providers and online merchants are added or removed from a large pool provided by a computing resource provider as need and depending on their needs.

The proliferation of network computing and storage, as well as the attendant increase in the number of entities dependent on network computing and storage, has increased the importance of optimizing data performance and integrity on network computing and storage systems. Data archival systems and services, for example, may use various types of error correcting and error tolerance schemes, such as the implementation of redundancy coding and data sharding. Furthermore, capacity and cost of persisting increasing quantities of data may be mitigated by the use of data storage devices or media that is considerably faster at sequential storage than random access storage, relative to other data storage devices.

BRIEF DESCRIPTION OF THE DRAWINGS

Various techniques will be described with reference to the drawings, in which:

FIG. 1 schematically illustrates an environment in which archives may be stored in a failure-decorrelated fashion on a data storage system implementing a redundancy code, in accordance with some embodiments;

FIG. 2 schematically illustrates a selector for data storage devices on a component of a data storage system, in accordance with some embodiments;

FIG. 3 schematically illustrates an example process for processing and storing data in a failure-decorrelated fashion on a data storage system, in accordance with some embodiments;

FIG. 4 schematically illustrates an example environment in which a computing resource service provider implements a data storage service to process and store data transacted therewith, in accordance with some embodiments;

FIG. 5 schematically illustrates an example process for indexing original data stored on a redundancy coded data storage system, in accordance with some embodiments;

FIG. 6 schematically illustrates an environment, including a computing resource service provider, in which data storage and indexing techniques may be implemented, in accordance with some embodiments;

FIG. 7 schematically illustrates a data storage service capable of implementing various data storage and indexing techniques, in accordance with some embodiments; and

FIG. 8 illustrates an environment in which various embodiments can be implemented.

DETAILED DESCRIPTION

In one example, original data of data archives (“archives”) are stored via data storage systems using redundancy coding techniques. For example, redundancy codes, such as erasure codes, may be applied to incoming archives (such as those received from a customer of a computing resource service provider implementing the storage techniques described herein) so as to allow the storage of original data of the individual archives available on a minimum of volumes, such as those of a data storage system, while retaining availability, durability, and other guarantees imparted by the application of the redundancy code.

In some embodiments, archives, such as customer archives containing any quantity and nature of data, are received from customers of a computing resource service provider through a service, such as an archival storage service, provided by one or more resources of the computing resource service provider. The archives may be sorted according to one or more common attributes, such as the identity of the customer, the time of upload and/or receipt by, e.g., the archival storage service. Such sorting may be performed so as to minimize the number of volumes on which any given archive is stored. In some embodiments, the original data of the archives is stored as a plurality of shards across a plurality of storage devices, the quantity of which (either shards or devices, which in some cases may have a one to one relationship) may be predetermined according to various factors, including the number of total shards sufficient to reconstruct the original data using a redundancy code.

In some embodiments, the data storage devices may be grouped in sets, each of which are colocated in a given component (such as a host) of a data storage system, and in some of such embodiments, the individual devices of a set of data storage devices of a host may be selected, randomly or otherwise, by a selector to store an incoming shard or portion thereof. The data storage system may include, depending on the redundancy coding scheme used, hosts or other components that, for a given set of shards, store original data of incoming archives, as well as hosts that store derived data (e.g., with mathematical transformations applied according to the implementing redundancy coding scheme). In some embodiments, the storage routines are implemented such that incoming archives to be stored in a given set of hosts are committed to a different set of storage devices relative to other archives, according to some apportionment scheme (e.g., based on an attribute of the incoming data itself, by random selection, by stochastic selection, deterministic selection, or other type of selection).

In some embodiments, the original data of the archives (and, in embodiments where the indices are stored on the volumes, the indices) is processed by an entity associated with, e.g., the archival storage service, using a redundancy code, such as an erasure code, so as to generate redundancy coded shards that may be used to regenerate the original data and, if applicable, the indices. In some embodiments, the redundancy code may utilize a matrix of mathematical functions (a “generator matrix”), a portion of which may include an identity matrix. In some of such embodiments, the redundancy coded shards may correspond, at least in part, to the portion of the generator matrix that is outside of the identity matrix. Redundancy coded shards so generated may be stored in further hosts and storage devices thereof.

In some embodiments, if one of the data storage devices or a shard stored thereon is detected as corrupt, missing, or otherwise unavailable, a new shard may be generated using the redundancy code applied to generate the shard(s) in the first instance. In some embodiments, the new shard may be a replication of the unavailable shard, such as may be the case if the shard includes original data of the archive(s). In some embodiments, the new shard may be selected from a set of potential shards as generated by, e.g., a generator matrix associated with the redundancy code, so as to differ in content from the unavailable shard (such as may be the case if the unavailable shard was a shard generated from the redundancy code, and therefore contains no original data of the archives). In such cases, in certain embodiments, an entirely new volume may be generated, rather than a shard.

An archive may be any data object or collection of data objects to be processed using the techniques described herein. For example, archives may be received by a customer of a system implementing the described techniques, for processing and storage therewith. Shards may be any quantity of data, such as a portion of a data object; for example, a plurality of shards may be generated as a result of encoding a data object using a redundancy code. A generator matrix may be a matrix of functions used by some of such redundancy codes, and used to encode a given data object (or portion thereof) into their encoded form (which, as may be contemplated, may be in the form of the aforementioned shards).

In the preceding and following description, various techniques are described. For purposes of explanation, specific configurations and details are set forth in order to provide a thorough understanding of possible ways of implementing the techniques. However, it will also be apparent that the techniques described below may be practiced in different configurations without the specific details. Furthermore, well-known features may be omitted or simplified to avoid obscuring the techniques being described.

FIG. 1 illustrates an example environment in which a generator matrix is used to generate initial grids of shards to be combined into a target grid, in accordance with some embodiments.

A customer device or other entity 102 connects with a data storage service, such as over a network, so as to transact sets of data 104, such as archives associated with the customer device, to be stored as, e.g., a bundle or grid of shards on hosts 106 associated with the data storage service. The incoming data 104 is processed by the data storage service using, e.g., a redundancy code implementing a generator matrix, so as to generate a bundle or grid of shards therefrom. The shards 110, 112 generated are submitted to the hosts 106 for storage on a set 114 of one or more data storage devices 108 associated with each host 106.

A selector, described in further detail in connection with FIG. 2, is employed to select amongst the set 114 of data storage devices for storage of a shard allocated for storage via that host. As described in further detail in FIG. 2, the selector performs the selection so as to decorrelate one or more failure modes or related failure events associated with components of the data storage system, the shards, or both.

In some embodiments, the redundancy code employed generates data shards 110 each having an original form of a subset of the incoming data 104, as well as derived shards 112 containing an encoded form of the subset. As described in further detail herein and in the incorporated disclosures, in such embodiments, a quorum quantity of the set of shards, regardless of whether they are data shards or derived shards, are usable to reconstruct any other shard within the set.

The customer device 102 may be any computing resource or collection of such resources enabling the customer to interface with the data storage system, such as in a programmatic fashion (e.g., via web service call or application programming interface call), and transact data therewith. Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), hardware or software-based storage devices (such as hard drives, optical drives, solid state devices, virtual storage devices such as provided by the computing resource service provider, and the like), services (e.g., such as those accessible via application programming interface calls, web service calls, or other programmatic methods), and the like.

The network may be a communication network, such as the Internet, an intranet or an Internet service provider (ISP) network. Some communications from the customer device to the data storage system may cause the data storage system to operate in accordance with one or more embodiments described or a variation thereof. The front end through which the data storage service, as well as other services as further described herein, operates, may be any entity capable of interfacing via the network with the customer device, as well as various other components of a data storage system, so as to coordinate and/or direct data and requests to the appropriate entities. Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), hardware or software-based storage devices (such as hard drives, optical drives, solid state devices, virtual storage devices such as provided by the computing resource service provider, and the like), services (e.g., such as those accessible via application programming interface calls, web service calls, or other programmatic methods), and the like.

The set of data 104 may be produced by a program, process, application, module, service, or system associated with a computing resource service provider as described herein. The set of data may also be produced by a user or customer of the computing resource service provider, and submitted to the computing resource service provider via a customer device and transmitted via a network. The set of data may include volatile data, which may be added to, changed, and/or deleted from in response to, for example, one or more requests (e.g., application programming interface requests or “API requests”) made by the user or customer of the computer system. The set of data may also include non-volatile data (also referred to herein as “static data”), which may be at least partially unchanging as the one or more requests are received.

The data stored across the durable storage volumes (e.g., data storage devices 108 and sets 114 thereof), may have an associated durability that may be based on, for example, an annual failure rate (“AFR”) of the data storage volume or the mapped data storage volume. For a given AFR, it may be assumed that the daily failure rate (“DFR”) for the data storage volume or the mapped data storage volume is the AFR divided by three-hundred and sixty-five (i.e., the number of days in a year) and the hourly failure rate (“HFR”) of the data storage volume or the mapped data storage volume is the DFR divided by twenty-four (i.e., the number of hours in a day). For example, if a data storage volume or the mapped data storage volume has an AFR of 2 percent, the data storage volume or the mapped data storage volume has a DFR of 0.0055 percent and an HFR of 0.00023 percent.

When the data is migrated or otherwise stored via the data storage service, the data storage service may store the data using one or more redundancy encoding techniques such as those described herein. For example, the data storage service may encode the data by producing one or more data shards 126, 130 and may store the one or more data shards on one or more volumes of a set of volumes of durable storage configured to store the redundancy encoded data as described herein. Depending on the redundancy encoding technique used by the data storage service, some or all of the shards stored may consist entirely of original data or derived data. In some embodiments, the shards may be apportioned on a one-to-one basis to the volumes of durable storage. Accordingly, in such embodiments, some volumes may include directly readable, original data (identity shards), while others contain only derived data (derived shards).

If, for example, a bundle of shards (whether alone or in a grid) has a minimum quorum quantity of two shards out of the three, any two of that row of shards—regardless of whether the shard is an identity shard or a derived shard, may be processed using the redundancy code so as to regenerate the data. Additionally, the original data may be regenerated by directly reading the identity shards.

It should be noted that, as used herein, the durability of data and/or data storage may be separate from the redundancy of the data in the data storage. For example, data stored in preliminary storage may be highly durable (i.e., have a very low failure rate) but may not be redundant if, for example, it is stored as a single copy. Conversely, data stored using one or more redundancy encoding techniques such as those described herein and while such data may be less durably stored (i.e., may have fewer “9's” of durability), it may be highly redundant. For example, data stored in a grid may have no fewer than four separate copies of the data (one of the data shard, one from the horizontally-derived shards, one from the vertically-derived shards, and one from the remaining shards). If the grid is geographically distributed into, for example, multiple datacenters in multiple geographic regions, the data may have greater redundancy due to the added tolerance for loss of a complete datacenter.

FIG. 2 schematically illustrates a selector for data storage devices on a component of a data storage system, in accordance with some embodiments.

Similarly to described above in connection with FIG. 1, an entity, such as a customer device 202, submits data 204 for storage on a host 206 of a data storage system. The host 206, as previously mentioned, may be one of a plurality of hosts across which the represented data is to be stored, and prior to storage, the data may be processed using a redundancy code so as to generate one or more shards 210. As a shard is submitted to the host 206 for storage, a selector, which may be a component of the host (or, in some embodiments, external to the host 206) selects a data storage device 208 from amongst a set of data storage devices 214 associated with the host 206, for storage of the allocated data (e.g., shard).

The selector 216 may use one or more techniques to make the selection. In some embodiments, the selector 216 is a physical device, such as a physical random number generator device. In some embodiments, the selector 216 is a software module or process operating upon the host 206, or on a different computing device associated with the host (e.g., of the computing resource service provider). The selector 216 may be a random number generator, which in some embodiments generates random numbers to make its selection. In some embodiments, the random number generator is a pseudorandom number generator (e.g., using algorithms to iteratively provide a set or sequence of numbers with correlation below a threshold set by the pseudorandom number generator). In some embodiments, the random number generator may draw upon entropy sources that are natural, artificial, or both. For example, the random number generator may use media entropy (e.g., spinning disk, tape noise, etc.), electronic noise entropy, time-based entropy, algorithms emulating entropy or randomness, or some combination thereof. In some embodiments, the random number generator is specifically decorrelated from time-based entropy sources.

The selector 216, in some embodiments, performs its selection using stochastic methods or deterministic methods. For example, the selector 216 may utilize a random number generator or other device that is weighted or biased based on operational considerations related to the data storage devices, such as capacity of the respective data storage devices between which the selector 216 is making its selection, load on the host, shard size or quantity incoming to the host, data type, and the like.

After selection, the selector 216 causes the host to store the specific subset of the data 204 for which it is making the selection 210 on the selected data storage device 208 of the set 214 associated with the host 206. In some embodiments, the next selection—e.g., for another subset of the data 204 or another set of data entirely, to be stored via the host 206—is made by the selector 216 independently of the prior selection. Thus, in such embodiments, the fact that a given data storage device 212 was not used in the last selection bears no weight in its potential future selection by the selector 216.

The effect of the selection made by the selector 216 may be that of decorrelation of one or more failure modes associated with storage of the data. For example, the failure mode may be as between failure events that are capable of affecting a plurality of data storage devices, across the set of data storage devices of the host, or across all data storage devices across all hosts on which the given piece of data is distributed. As another example, the decorrelated failure mode may be as between hosts of the set of hosts on which the data is to be stored. As another example, the decorrelated failure mode may be as between shards, such as generated using a redundancy code. The failure mode decorrelation performed using the techniques described in this disclosure are combinable with other failure mode decorrelation techniques, such as those described in the incorporated disclosures.

FIG. 3 schematically illustrates an example process for processing and storing data in a failure-decorrelated fashion on a data storage system, in accordance with some embodiments.

At step 302, a host or other entity receives a redundancy coded shard, such as those generated from customer data using one or more redundancy codes applied by a data storage system, for storage. The shard may be of a set of redundancy coded shards distributed between multiple hosts.

At step 304, a selector or other entity, such as those described above in connection with FIGS. 1 and 2, determine an appropriate device selection scheme so as to decorrelate one or more failure modes (e.g., by disassociating a failure event relative to the components the event affects, and/or by disassociating multiple related failure events relative to one another) associated with the system. The determined scheme may take into account the failure characteristics or failure events associated with the failure mode, such as media failure, host failure, correlated media failure, correlated host failure, shard corruption, and the like.

At step 306, the selector or other entity performs the selection of the device, using the device selection scheme determined in step 304, from amongst a set of devices associated with the host, and at step 308, the host stores the received shard on the device selected in step 306. As previously mentioned, the selection may be made randomly (either fully randomly or pseudorandomly), stochastically, deterministically, or by some combination of those approaches.

At step 310, data stored in accordance with steps 302-308 may be located, such as by the data storage system and/or data storage service, by locating information that locates the stored data in the indices related to the data (e.g., as described in connection with at least FIGS. 6-7 below) and used for further retrieval of the data. For example, a bloom filter or similar probabilistic data structure may be used so as to quickly traverse (e.g., by the data storage system) the contents of a given data storage device, so as to locate the requested data or shard associated therewith on the data storage device on which it was previously stored, e.g., randomly or pseudorandomly in accordance with other techniques described herein.

FIG. 4 illustrates an example environment in which a computing resource service provider implements a data storage service, such as a grid storage service, to process and store data transacted therewith, in accordance with some embodiments.

A customer, via a customer device 402, may connect via a network 404 to one or more services 406 provided by a computing resource service provider 418. In some embodiments, the computing resource service provider 418 may provide a distributed, virtualized and/or datacenter environment within which one or more applications, processes, services, virtual machines, and/or other such computer system entities may be executed. In some embodiments, the customer may be a person, or may be a process running on one or more remote computer systems, or may be some other computer system entity, user, or process. The customer device 402 and the network 404 may be similar to that described in connection with at least FIG. 1 above.

The command or commands to connect to the computer system instance may originate from an outside computer system and/or server, or may originate from an entity, user, or process on a remote network location, or may originate from an entity, user, or process within the computing resource service provider, or may originate from a user of the customer device 402, or may originate as a result of an automatic process or may originate as a result of a combination of these and/or other such origin entities. In some embodiments, the command or commands to initiate the connection to the computing resource service provider 418 may be sent to the services 406, without the intervention of the user of the services 406. The command or commands to initiate the connection to the services 406 may originate from the same origin as the command or commands to connect to the computing resource service provider 418 or may originate from another computer system and/or server, or may originate from a different entity, user, or process on the same or a different remote network location, or may originate from a different entity, user, or process within the computing resource service provider, or may originate from a different user of the customer device 402, or may originate as a result of a combination of these and/or other such same and/or different entities.

The customer device 402 may request connection to the computing resource service provider 418 via one or more connections and, in some embodiments, via one or more networks 404 and/or entities associated therewith, such as servers connected to the network, either directly or indirectly. The customer device 402 that requests access to the services 406 may, as previously discussed, include any device that is capable of connecting with a computer system via a network, including at least servers, laptops, mobile devices such as smartphones or tablets, other smart devices such as smart watches, smart televisions, set-top boxes, video game consoles and other such network-enabled smart devices, distributed computer systems and components thereof, abstracted components such as guest computer systems or virtual machines and/or other types of computing devices and/or components. The network 404, also as previously discussed, may include, for example, a local network, an internal network, a public network such as the Internet, or other networks such as those listed or described herein. The network may also operate in accordance with various protocols such as those listed or described herein.

The computing resource service provider 418 may provide access to one or more host machines as well as provide access to services such as virtual machine (VM) instances, automatic scaling groups, or file-based database storage systems as may be operating thereon. The services 406 may connect to or otherwise be associated with one or more storage services such as those described herein (e.g., the data storage service 414). The storage services may be configured to provide data storage for the services 406. In an embodiment, the computing resource service provider 418 may provide direct access to the one or more storage services for use by users and/or customers of the computing resource service provider. The storage services may manage storage of data on one or more block storage devices and/or may manage storage of data on one or more archival storage devices such as, for example, magnetic tapes.

For example, the computing resource service provider 418 may provide a variety of services 406 to the customer device 402, which may in turn communicate with the computing resource service provider 418 via an interface, which may be a web service interface, application programming interface (API), user interface, or any other type of interface. The services 406 provided by the computing resource service provider 418 may include, but may not be limited to, a virtual computer system service, a block-level data storage service, a cryptography service, an on-demand data storage service, a notification service, an authentication service, a policy management service, an archival storage service, a durable data storage service such as the data storage service 414, and/or other such services. Each of the services 406 provided by the computing resource service provider 418 may include one or more web service interfaces that enable the customer device 402 to submit appropriately configured API calls to the various services through web service requests. In addition, each of the services may include one or more service interfaces that enable the services to access each other (e.g., to enable a virtual computer system of the virtual computer system service to store data in or retrieve data from the on-demand data storage service or the data storage service 414, and/or to access one or more block-level data storage devices provided by the block-level data storage service).

The block-level data storage service may comprise one or more computing resources that collectively operate to store data for a user using block-level storage devices (and/or virtualizations thereof). The block-level storage devices of the block-level data storage service may, for example, be operationally attached to virtual computer systems provided by a virtual computer system service to serve as logical units (e.g., virtual drives) for the computer systems. A block-level storage device may enable the persistent storage of data used or generated by a corresponding virtual computer system where the virtual computer system service may be configured to only provide ephemeral data storage.

The computing resource service provider 418 may also include an on-demand data storage service. The on-demand data storage service may be a collection of computing resources configured to synchronously process requests to store and/or access data. The on-demand data storage service may operate using computing resources (e.g., databases) that enable the on-demand data storage service to locate and retrieve data quickly, to allow data to be provided in response to requests for the data. For example, the on-demand data storage service may maintain stored data in a manner such that, when a request for a data object is retrieved, the data object can be provided (or streaming of the data object can be initiated) in a response to the request. As noted, data stored in the on-demand data storage service may be organized into data objects. The data objects may have arbitrary sizes except, perhaps, for certain constraints on size. Thus, the on-demand data storage service may store numerous data objects of varying sizes. The on-demand data storage service may operate as a key value store that associates data objects with identifiers of the data objects that may be used by the user to retrieve or perform other operations in connection with the data objects stored by the on-demand data storage service.

Note that, unless otherwise specified, use of expressions regarding executable instructions (also referred to as code, applications, agents, etc.) performing operations that instructions do not ordinarily perform unaided (e.g., transmission of data, calculations, etc.) in the context of describing disclosed embodiments denote that the instructions are being executed by a machine, thereby causing the machine to perform the specified operations.

The services 406 may produce data, such as data 408 received from the customer device 402, which may be stored 422 in the preliminary storage 412 as described above. In some embodiments, as previously mentioned, the data stored in the preliminary storage may be stored in unaltered form, such as in an identity shard. While the data is stored in the preliminary storage 412, the data 422 may be accessed by the services 406 (e.g., as a result of one or more API requests by the customer device 402) from the preliminary storage 412. After a determined period 420 has passed and the data is migrated to a data storage service 414 provided by the computing resource service provider 418, the data may be accessed using the data storage service 414. In an embodiment where the data may be stored using redundancy encoding technique such as those described herein, the data storage service 414 may retrieve the data from any of the data volumes 416 and/or may reconstruct the data using the redundancy encoding techniques. The data volumes 416 may be magnetic tape, may be optical disks, or may be some other such storage media. As previously discussed and as further discussed herein, the data may be stored in identity shards that correspond individually to volumes, and may also be processed (using the redundancy encoding techniques) so as to create derived shards.

The data storage service 414 may store the data 422 in the preliminary storage 412 or may transmit a command that causes a different service (e.g., a block storage service or some other storage service such as those described herein) to store the data 422 in the preliminary storage 412. The data storage service 414 may also cause the data to be migrated from the preliminary storage 412 or may transmit a command that causes a different service to cause the data to be migrated from the preliminary storage 412. The data storage service 414 may also transmit a command or commands to cause a different service to perform other operations associated with making data objects eventually durable including, but not limited to, storing the data objects in the data shards, calculating derived shards, updating bundles, updating grids (i.e., updating horizontal, vertical, and other bundles of multiply bundled data), and/or other such operations.

In an embodiment, the preliminary storage 412 is a data storage volume such as, for example, a magnetic disk drive (e.g., a spinning disk drive or a solid state disk drive), computer system memory, magnetic tape, or some other optical storage device. In another embodiment, the preliminary storage 412 is a virtual and/or shared data storage volume that is mapped to a physical storage volume such as, for example, a disk drive, a solid state disk drive, computer system memory, magnetic tape, or some other optical storage device. As may be contemplated, the types of data storage volumes used for the preliminary storage 412 described herein are illustrative examples and other types of data storage volumes used for the preliminary storage may be considered as within the scope of the present disclosure.

In an embodiment, the preliminary storage 412 is a plurality of storage devices that are used to redundantly store the data using techniques such as, for example, bundle encoding, grid encoding, or replicated storage. For example, the preliminary storage 412 may store the data by distributing the data to a plurality of data shards (e.g., putting a first portion of the data in a first data shard and a second portion of the data in a second data shard) and generating one or more derived shards based on those data shards. In another embodiment, the preliminary storage 112 is one or more storage devices that store redundant copies of the data as received. In yet another embodiment, the preliminary storage uses a combination of the storage techniques described herein by, for example, storing a single copy of the data for a first time period (e.g., thirty minutes), storing multiple copies of the data for a second time period (e.g., one day), using redundant storage techniques such as grid or bundle encoding to store the data for a third time period (e.g., thirty days), and then moving the data to more durable storage 416 using the data storage service 414 as described herein.

The set of data may be stored in the preliminary storage 412 in an unaltered form (e.g., not processed, compressed, indexed, or altered prior to storage). The set of data may also be stored in the preliminary storage 412 as, for example, original data (also referred to herein as an “identity shard”) such as the original data shards described herein. In an embodiment, the set of data stored in the preliminary storage 412 is stored without indexing and without any redundancy encoding. In another embodiment, the set of data stored in the preliminary storage 412 is stored with null redundancy encoding (i.e., a redundancy encoding that maps the data to itself). The data in preliminary storage may be stored as raw data, or may be bundle-encoded, or may be grid-encoded, or may be stored using some other method.

In an embodiment, data can be migrated from preliminary storage to the data storage service 412 as a result of an event such as, for example, a request by a customer to store the data in the data storage service 414. Other events may also be used to cause the migration of the data from preliminary storage 412 to the data storage service 414 such as, for example, events generated by a process, module, service, or application associated with the customer or associated with a computing resource service provider. In an illustrative example, a block storage service may maintain data storage in preliminary storage for a running virtual machine instance and, upon termination of the instance, may generate an event to migrate some or all of the data from preliminary storage to durable storage. The triggering event that causes the migration of data from preliminary storage may also be combined with an elapsed time as described above so that, for example, data may be stored in preliminary storage until an event occurs, but the data may also be migrated from preliminary storage if no event occurs prior to the elapsed time. As may be contemplated, the criteria for initiating the migration from preliminary storage described herein are illustrative examples and other such criteria for initiating the migration from preliminary storage may be considered as within the scope of the present disclosure.

As used herein, the durability of a data object may be understood to be an estimate of the probability that the data object will not unintentionally become permanently irretrievable (also referred to herein as “unavailable”). This durability is an estimated probability and is generally expressed as a percentage (e.g., 99.9999 percent). This durability is based on assumptions of probabilities of certain failures (e.g., the AFR of drives used to store the data) and may be based on an average failure rate, a maximum failure rate, a minimum failure rate, a mean failure rate, or some other such failure rate. The durability may be based on a statistical average of the failure over a collection of drives when there are many different drives and/or when there are many different types of drives. The durability may also be based on historical measurements of the failure of drives and/or statistical sampling of the historical measurements of the failure of drives. The durability may also be correlated with the probability that a data object will not unintentionally become unavailable such as, for example, basing the durability on the probability that a data object will unintentionally become unavailable. As may be contemplated, the methods of determining durability of data described herein are merely illustrative examples and other such methods of determining durability of data may be considered as within the scope of the present disclosure.

In an embodiment, a separate service 410 can be configured to monitor the elapsed time 420 associated with the data objects in preliminary storage 412 and, based on a desired durability, cause the data storage service 414 to cause the data to be migrated from the preliminary storage 412 to the durable storage by, for example, transmitting a message to the data storage service. This separate service may operate asynchronously to enforce time limits for all such data stored in preliminary storage.

FIG. 5 illustrates an example environment 500 where a redundancy encoding technique is applied to data stored in durable storage as described in connection with FIGS. 1-7 and in accordance with an embodiment. The redundancy encoding technique illustrated in FIG. 5 is an example of a grid encoding technique wherein each identity shard is part of a first set of one or more identity shards which may be bundled with one or more derived shards in a first group or bundle (i.e., in one dimension or direction) and each identity shard is also part of at least a second set of one or more identity shards which may be bundled with one or more other derived shards in a second bundle or group (i.e., in a second dimension or direction). As is illustrated in FIG. 5, a grid encoding technique is often implemented as a two-dimensional grid, with each shard being part of two bundles (i.e., both “horizontal” and “vertical” bundles). However, a grid encoding technique may also be implemented as a three-dimensional grid, with each shard being part of three bundles, or a four-dimensional grid, with each shard being part of four bundles, or as a larger-dimensional grid. Additional details of grid encoding techniques are described in U.S. patent application Ser. No. 14/789,783, filed Jul. 1, 2015, entitled “GRID ENCODED DATA STORAGE SYSTEMS FOR EFFICIENT DATA REPAIR”, which is incorporated by reference herein.

In the example illustrated in FIG. 5, data 502 from preliminary storage is provided for storage in durable storage using a redundancy encoding technique with both horizontal derived shards and vertical derived shards. In the example illustrated in FIG. 5, a first datacenter 512 may contain data shards (denoted as a square shard with the letter “I”), horizontal derived shards (denoted as a triangular shard with the Greek letter “δ” or delta), and vertical derived shards (denoted as an inverted triangle with the Greek letter “δ”) all of which may be stored on durable storage volumes within the first datacenter 512. A second datacenter 514, which may be geographically and/or logically separate from the first datacenter 512, may also contain data shards, horizontal derived shards, and/or vertical derived shards. A third datacenter 516, which may be geographically and/or logically separate from the first datacenter 512 and from the second datacenter 514, may also contain data shards, horizontal derived shards, and/or vertical derived shards. As illustrated in FIG. 5, each of the three datacenters may be a single vertical bundle. In an embodiment, each of the datacenters can include multiple vertical bundles. As may be contemplated, the number of datacenters illustrated in FIG. 5 and/or the composition of the datacenters illustrated in FIG. 5 are merely illustrative examples and other numbers and/or compositions of datacenters may be considered as within the scope of the present disclosure. The datacenters may be co-located or may be located in one or more separate datacenter locations.

In the example illustrated in FIG. 5, the data 502 may be copied to a data shard 504 and, as a result of the change to the data in the data shard 504, a horizontal derived shard 506 associated with the data shard 504 may be updated so that the horizontal derived shard 506 may be used to reconstruct the data shard 504 in the event of a loss of the data shard 504. In the example illustrated in FIG. 5, the three shards enclosed by the dotted line (e.g., the data shard 504, the data shard 520, and the horizontal derived shard 506) are a horizontal bundle 518. In this example, the data shard 520 is not affected by the changes to the data shard 504 but the horizontal derived shard 506 may need to be updated as a result of the changes to the data shard 504.

Also as a result of the change to the data in the data shard 504, one or more vertical derived shards 508 related to the data shard 504 may also be updated so that the vertical derived shards 508 may be used to reconstruct the data shard 504 in the event of a loss of the data shard 504 and the horizontal derived shard 506. In the example illustrated in FIG. 5, the shards in datacenter 512 form a vertical bundle. In this example, the other data shards 522 in the vertical bundle and/or the horizontal derived shards 524 in the vertical bundle are not affected by the changes to the data shard 504 but the vertical derived shards 508 may need to be updated as a result of the changes to the data shard 504. Finally, as a result of the change to the horizontal derived shard 506, one or more vertical derived shards 510 related to the horizontal derived shard 506 in the vertical bundle in datacenter 516 may also be updated so that the vertical derived shards 510 may be used to reconstruct the horizontal derived shard 506 in the event of a loss of the horizontal derived shard 506 and the data shard 504.

FIG. 6 illustrates an example environment 600 where a redundancy encoding technique is applied to data stored in durable storage as described herein and in accordance with at least one embodiment. The redundancy encoding technique illustrated in FIG. 6 is an example of a bundle encoding technique wherein one or more identity shards (also referred to herein as “data shards”) may be bundled with one or more derived shards in a single group or dimension. Additional details of bundle encoding techniques are described in U.S. patent application Ser. No. 14/741,409, filed Jun. 16, 2015, entitled “ADAPTIVE DATA LOSS MITIGATION FOR REDUNDANCY CODING SYSTEMS,” which is incorporated by reference herein.

Data 602 from preliminary storage may be sent to a data storage system 604 for redundant storage. The data 602 may be provided from the preliminary storage by any entity capable of transacting data with a data storage system, such as over a network (including the Internet). Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), services (e.g., such as those connecting to the data storage system 604 via application programming interface calls, web service calls, or other programmatic methods), and the like.

The data storage system 604 may be any computing resource or collection of such resources capable of processing data for storage, and interfacing with one or more resources to cause the storage of the processed data. Examples include physical computing systems (e.g., servers, desktop computers, laptop computers, thin clients, and handheld devices such as smartphones and tablets), virtual computing systems (e.g., as may be provided by the computing resource service provider using one or more resources associated therewith), services (e.g., such as those connecting to the data storage system 604 via application programming interface calls, web service calls, or other programmatic methods), and the like. In some embodiments, the resources of the data storage system 604, as well as the data storage system 604 itself, may be one or more resources of a computing resource service provider, such as that described in further detail below. In some embodiments, the data storage system 604 and/or the computing resource service provider provides one or more archival storage services and/or data storage services, such as those described herein, through which a client entity may provide data such as the data 602 for storage in preliminary storage and/or the data storage system 604.

Data 602 may include any quantity of data in any format. For example, the data 602 may be a single file or may include several files. The data 602 may also be encrypted by, for example, a component of the data storage system 604 after the receipt of the data 602 in response to a request made by a customer of the data storage system 604 and/or by a customer of computing resource service provider.

The data storage system 604 may sort one or more identity shards according to one or more criteria (and in the case where a plurality of criteria is used for the sort, such criteria may be sorted against sequentially and in any order appropriate for the implementation). Such criteria may be attributes common to some or all of the archives, and may include the identity of the customer, the time of upload and/or receipt (by the data storage system 604), archive size, expected volume and/or shard boundaries relative to the boundaries of the archives (e.g., so as to minimize the number of archives breaking across shards and/or volumes), and the like. As mentioned, such sorting may be performed so as to minimize the number of volumes on which any given archive is stored. Such techniques may be used, for example, to optimize storage in embodiments where the overhead of retrieving data from multiple volumes is greater than the benefit of parallelizing the retrieval from the multiple volumes. Information regarding the sort order may be persisted, for example, by the data storage system 604, for use in techniques described in further detail herein.

As previously discussed, in some embodiments, one or more indices may be generated in connection with, for example, the order in which the archives are to be stored, as determined in connection with the sorting mentioned immediately above. The index may be a single index or may be a multipart index, and may be of any appropriate architecture and may be generated according to any appropriate method. For example, the index may be a bitmap index, dense index, sparse index, or a reverse index. Embodiments where multiple indices are used may implement different types of indices according to the properties of the identity shard to be stored via the data storage system 604. For example, a data storage system 604 may generate a dense index for archives over a specified size (as the size of the index itself may be small relative to the number of archives stored on a given volume), and may also generate a sparse index for archives under that specified size (as the ratio of index size to archive size increases).

The data storage system 604 is connected to or includes one or more volumes 606 on which archives or identity shards may be stored. The generated indices for the archives may also be stored on the one or more volumes 606. The volumes 606 may be any container, whether logical or physical, capable of storing or addressing data stored therein. In some embodiments, the volumes 606 may map on a one-to-one basis with the data storage devices on which they reside (and, in some embodiments, may actually be the data storage devices themselves). In some embodiments, the size and/or quantity of the volumes 606 may be independent of the capacity of the data storage devices on which they reside (e.g., a set of volumes may each be of a fixed size such that a second set of volumes may reside on the same data storage devices as the first set). The data storage devices may include any resource or collection of resources, such as those of a computing resource service provider, that are capable of storing data, and may be physical, virtual, or some combination of the two.

As previously described, one or more indices may, in some embodiments, be generated for each volume of the plurality of volumes 606, and in such embodiments, may reflect the archives stored on the respective volume to which it applies. In embodiments where sparse indices are used, a sparse index for a given volume may point to a subset of archives stored or to be stored on that volume, such as those archives which may be determined to be stored on the volume based on the sort techniques mentioned previously. The subset of volumes to be indexed in the sparse index may be selected on any appropriate basis and for any appropriate interval. For example, the sparse index may identify the archives to be located at every x blocks or bytes of the volume (e.g., independently of the boundaries and/or quantity of the archives themselves). As another example, the sparse index may identify every nth archive to be stored on the volume. As may be contemplated, the indices (whether sparse or otherwise), may be determined prior to actually storing the archives on the respective volumes. In some embodiments, a space may be reserved on the volumes so as to generate and/or write the appropriate indices after the archives have been written to the volumes 606.

In some embodiments, the sparse indices are used in connection with information relating to the sort order of the archives so as to locate archives without necessitating the use of dense indices, for example, those that account for every archive on a given volume. Such sort order-related information may reside on the volumes 606 or, in some embodiments, on an entity separate from the volumes 606, such as in a data store or other resource of a computing resource service provider. Similarly, the indices may be stored on the same volumes 606 to which they apply, or, in some embodiments, separately from such volumes 606.

The archives may be stored, bit for bit (e.g., the “original data” of the archives), on a subset of the plurality of volumes 606. Also as mentioned, appropriate indices may also be stored on the applicable subset of the plurality of volumes 606. The original data of the archives is stored as a plurality of shards across a plurality of volumes, the quantity of which (either shards or volumes, which in some cases may have a one to one relationship) may be predetermined according to various factors, including the number of total shards that may be used to reconstruct the original data using a redundancy encode. In some embodiments, the number of volumes used to store the original data of the archives is the quantity of shards that may be used to reconstruct the original data from a plurality of shards generated by a redundancy code from the original data. As an example, FIG. 6 illustrates five volumes, three of which contain original data archives 608 and two of which contain derived data 610, such as redundancy encoded data. In the illustrated example, the redundancy code used may require any three shards to regenerate original data, and therefore, a quantity of three volumes may be used to write the original data (even prior to any application of the redundancy code).

The volumes 606 bearing the original data archives 608 may each contain or be considered as shards unto themselves. For example, the data 602 from preliminary storage may be copied directly only to a volume if, as described herein, it is stored in preliminary storage as an identity shard. In embodiments where the sort order-related information and/or the indices are stored on the applicable volumes 606, they may be included with the original data of the archives and stored therewith as shards, as previously mentioned. In the illustrated example, the original data archives 608 are stored as three shards (which may include the respective indices) on three associated volumes 606. In some embodiments, the original data archives 608 (and, in embodiments where the indices are stored on the volumes, the indices) are processed by an entity associated with, for example, the archival storage service, using a redundancy code, such as an erasure code, so as to generate the remaining shards, which contain encoded information rather than the original data of the original data archives. The original data archives 608 may be processed using the redundancy code at any time after being sorted, such as prior to being stored on the volumes, contemporaneously with such storage, or after such storage.

Such encoded information may be any mathematically computed information derived from the original data, and depends on the specific redundancy code applied. As mentioned, the redundancy code may include erasure codes (such as online codes, Luby transform codes, raptor codes, parity codes, Reed-Solomon codes, Cauchy codes, Erasure Resilient Systematic Codes, regenerating codes, or maximum distance separable codes) or other forward error correction codes. In some embodiments, the redundancy code may implement a generator matrix that implements mathematical functions to generate multiple encoded objects correlated with the original data to which the redundancy code is applied. In some of such embodiments, an identity matrix is used, wherein no mathematical functions are applied and the original data (and, if applicable, the indices) are allowed to pass straight through. In such embodiments, it may be therefore contemplated that the volumes bearing the original data (and the indices) may correspond to objects encoded from that original data by the identity matrix rows of the generator matrix of the applied redundancy code, while volumes bearing derived data correspond to other rows of the generator matrix. In the example illustrated in FIG. 6, the five volumes 606 include three volumes that have shards (e.g., identity shards) corresponding to the original data of the original data archives 608, while two have encoded shards corresponding to the derived data 610 (also referred to herein as “derived shards”). As illustrated in FIG. 6, the three original data archives 608, and the two encoded shards corresponding to the derived data 610 form a bundle 618 (denoted by the dashed line). In this example, the applied redundancy code may result in the data being stored in a “3:5” scheme, wherein any three shards of the five stored shards are required to regenerate the original data, regardless of whether the selected three shards contain the original data or the derived data.

In some embodiments, if one of the volumes 606 or a shard stored thereon is detected as corrupt, missing, or otherwise unavailable, a new shard may be generated using the redundancy code applied to generate the shard(s) in the first instance. The new shard may be stored on the same volume or a different volume, depending, for example, on whether the shard is unavailable for a reason other than the failure of the volume. The new shard may be generated by, for example, the data storage system 604, by using a quantity of the remaining shards that may be used to regenerate the original data (and the index, if applicable) stored across all volumes, regenerating that original data, and either replacing the portion of the original data corresponding to that which was unavailable (in the case that the unavailable shard contains original data), or reapplying the redundancy code so as to provide derived data for the new shard.

As previously discussed, in some embodiments, the new shard may be a replication of the unavailable shard, such as may be the case if the unavailable shard includes original data of the archive(s). In some embodiments, the new shard may be selected from a set of potential shards as generated by, for example, a generator matrix associated with the redundancy code, so as to differ in content from the unavailable shard (such as may be the case if the unavailable shard was a shard generated from the redundancy code, and therefore contains no original data of the archives). As discussed throughout this disclosure, the shards and/or volumes may be grouped and/or layered.

In some embodiments, retrieval of an archive stored in accordance with the techniques described herein may be requested by a client entity under control of a customer of the computing resource service provider and/or the archival storage service provided therefrom, as described in further detail throughout this disclosure. In response to the request, the data storage system 604 may locate, based on information regarding the sort order of the archives as stored on the volumes 606, the specific volume on which the archive is located. Thereafter, the index or indices may be used to locate the specific archive, whereupon it may be read from the volume and provided to a requesting client entity. In embodiments where sparse indices are employed, the sort order information may be used to locate the nearest location (or archive) that is sequentially prior to the requested archive, whereupon the volume is sequentially read from that location or archive until the requested archive is found. In embodiments where multiple types of indices are employed, the data storage system 604 may initially determine which of the indices includes the most efficient location information for the requested archive based on assessing the criteria used to deploy the multiple types of indices in the first instance. For example, if archives under a specific size are indexed in a sparse index and archives equal to or over that size are indexed in a parallel dense index, the data storage system 604 may first determine the size of the requested archive, and if the requested archive is larger than or equal to the aforementioned size boundary, the dense index may be used so as to more quickly obtain the precise location of the requested archive.

In some embodiments, the volumes 606 may be grouped such that each given volume has one or more cohorts 616. In such embodiments, a volume set (e.g., all of the illustrated volumes 606) may be implemented such that incoming archives to be stored on the volumes are apportioned to one or more failure-decorrelated subsets of the volume set. The failure-decorrelated subsets may be some combination of the volumes 606 of the volume subset, where the quantity of volumes correlates to a number of shards required for the implemented redundancy code. In the illustrated example, the overall volume set may comprise two failure-decorrelated subsets (volumes in a horizontal row) where a given constituent volume is paired with a cohort (e.g., the cohort 616). In some embodiments, the incoming archives are apportioned to one or more of the cohorts in the failure-decorrelated subset according to, for example, a predetermined sequence, based on one or more attributes of the incoming archives, and the like.

The illustrated example shows, for clarity, a pair-wise cohort scheme, though other schemes are contemplated as within scope of this disclosure, some of which are outlined in greater detail herein. In the illustrated example, some of the volumes of the volume set store original data of incoming archives (e.g., original data archives 608 and/or original data archives 612), while others store derived data (e.g., derived data 610 and derived data 614). The data storage system 604 may implement a number of failure-decorrelated subsets to which to store the incoming archives, and in the pair-wise scheme pictured, the volumes used for a given archive may differ based on some arbitrary or predetermined pattern. As illustrated, some archives may be apportioned to volumes of a given cohort that are assigned to one pattern, or failure-decorrelated subset as shown by original data archives 608 and derived data 610, while others are apportioned to volumes in a different pattern as shown by original data archives 612 and derived data 614. The patterns, as mentioned, may be arbitrary, predefined, and/or in some cases, sensitive to attributes of the incoming data. In some embodiments, patterns may not be used at all, and the member volumes of a given failure-decorrelated subset may be selected randomly from a pool of volumes in the volume set.

FIG. 7 illustrates an example process 700 for applying redundancy encoding techniques to data stored in durable storage as described herein in connection with FIG. 1 and in accordance with at least one embodiment. The example process 700 illustrated in FIG. 7 illustrates the processing, indexing, storing, and retrieving of data stored on a data storage system. The data may be retrieved from preliminary storage as described herein. The example process 700 illustrated in FIG. 7 may be used in conjunction with a grid encoding technique such that described in connection with FIG. 5, in conjunction with a bundle encoding technique such as that described in connection with FIG. 6, or with some other redundancy encoding technique. A data storage service such as the data storage service described herein may perform the example process 700 illustrated in FIG. 7.

At step 702, a resource of a data storage system, such as that implementing a redundancy code to store archives, determines which subset (e.g., quantity) of a plurality of volumes that may be used to recreate the original data to be stored, based on, for example, a redundancy code to be applied to the archives. For example, in accordance with the techniques described above in connection with FIG. 6, such information may be derived from predetermining the parameters of an erasure code with a specified ratio of shards that may be used to regenerate the original data from which they derive to the total number of shards generated from the application of the erasure code.

At step 704, original data, such as original data of archives received from customers of, for example, a data storage system or a computing resource service provider as described in further detail herein, is sorted by, for example, the data storage system or associated entity. For example, the sort order may be implemented on one or more attributes of the incoming data.

At step 706, one or more indices, such as sparse indices, are generated by, for example, the data storage system, for the original data. For example, there may be more than one index for a given volume, and such parallel indices may be of different types depending on the nature of the archives and/or original data being stored.

At step 708, the original data is stored, for example, by the data storage system, on the subset of volumes determined in connection with step 702, and in the order determined in step 704. Additionally, at step 710, the index generated in step 706 is stored, for example, by the data storage system, on an appropriate entity. For example, the index may be stored as part of a shard on which the original data is stored, or, in some embodiments, may be stored on a separate resource from that which persists the volume.

At step 712, the redundancy code is applied, for example, by the data storage system, to the determined subset of volumes (e.g., shards, as previously described herein), and additional shards containing data derived from the application of the redundancy code are stored on a predetermined quantity of volumes outside the subset determined in connection with step 702. For example, the ratio of volumes (e.g., shards as previously described herein) storing the original data to the overall quantity of volumes (including those storing the derived data generated in this step 712) may be prescribed by the recovery/encoding ratio of the redundancy code applied herein.

At step 714, in normal operation, requested data may be retrieved, for example, by the data storage system, directly from the subset of volumes storing the original data, without necessitating retrieval and further processing (e.g., by the redundancy code) from the volumes storing the derived data generated in step 712. However, at step 716, if any of the volumes are determined, for example, by the data storage system, to be unavailable, a replacement shard may be generated by the data storage system by reconstructing the original data from a quorum of the remaining shards, and re-encoding using the redundancy code to generate the replacement shard. The replacement shard may be the same or may be different from the shard detected as unavailable.

FIG. 8 illustrates aspects of an example environment 800 for implementing aspects in accordance with various embodiments. As will be appreciated, although a web-based environment is used for purposes of explanation, different environments may be used, as appropriate, to implement various embodiments. The environment includes an electronic client device 802, which can include any appropriate device operable to send and/or receive requests, messages, or information over an appropriate network 804 and, in some embodiments, convey information back to a user of the device. Examples of such client devices include personal computers, cell phones, handheld messaging devices, laptop computers, tablet computers, set-top boxes, personal data assistants, embedded computer systems, electronic book readers, and the like. The network can include any appropriate network, including an intranet, the Internet, a cellular network, a local area network, a satellite network or any other such network and/or combination thereof. Components used for such a system can depend at least in part upon the type of network and/or environment selected. Many protocols and components for communicating via such a network are well known and will not be discussed herein in detail. Communication over the network can be enabled by wired or wireless connections and combinations thereof. In this example, the network includes the Internet and/or other publicly-addressable communications network, as the environment includes a web server 806 for receiving requests and serving content in response thereto, although for other networks an alternative device serving a similar purpose could be used as would be apparent to one of ordinary skill in the art.

The illustrative environment includes at least one application server 808 and a data store 810. It should be understood that there can be several application servers, layers or other elements, processes or components, which may be chained or otherwise configured, which can interact to perform tasks such as obtaining data from an appropriate data store. Servers, as used herein, may be implemented in various ways, such as hardware devices or virtual computer systems. In some contexts, servers may refer to a programming module being executed on a computer system. As used herein, unless otherwise stated or clear from context, the term “data store” refers to any device or combination of devices capable of storing, accessing and retrieving data, which may include any combination and number of data servers, databases, data storage devices and data storage media, in any standard, distributed, virtual or clustered environment. The application server can include any appropriate hardware, software and firmware for integrating with the data store as needed to execute aspects of one or more applications for the client device, handling some or all of the data access and business logic for an application. The application server may provide access control services in cooperation with the data store and is able to generate content including, but not limited to, text, graphics, audio, video and/or other content usable to be provided to the user, which may be served to the user by the web server in the form of HyperText Markup Language (“HTML”), Extensible Markup Language (“XML”), JavaScript, Cascading Style Sheets (“CSS”), JavaScript Object Notation (JSON), and/or another appropriate client-side structured language. Content transferred to a client device may be processed by the client device to provide the content in one or more forms including, but not limited to, forms that are perceptible to the user audibly, visually and/or through other senses. The handling of all requests and responses, as well as the delivery of content between the client device 802 and the application server 808, can be handled by the web server using PHP: Hypertext Preprocessor (“PHP”), Python, Ruby, Perl, Java, HTML, XML, JSON, and/or another appropriate server-side structured language in this example. Further, operations described herein as being performed by a single device may, unless otherwise clear from context, be performed collectively by multiple devices, which may form a distributed and/or virtual system.

The data store 810 can include several separate data tables, databases, data documents, dynamic data storage schemes and/or other data storage mechanisms and media for storing data relating to a particular aspect of the present disclosure. For example, the data store illustrated may include mechanisms for storing production data 812 and user information 816, which can be used to serve content for the production side. The data store also is shown to include a mechanism for storing log data 814, which can be used for reporting, analysis or other such purposes. It should be understood that there can be many other aspects that may need to be stored in the data store, such as page image information and access rights information, which can be stored in any of the above listed mechanisms as appropriate or in additional mechanisms in the data store 810. The data store 810 is operable, through logic associated therewith, to receive instructions from the application server 808 and obtain, update or otherwise process data in response thereto. The application server 808 may provide static, dynamic, or a combination of static and dynamic data in response to the received instructions. Dynamic data, such as data used in web logs (blogs), shopping applications, news services and other such applications may be generated by server-side structured languages as described herein or may be provided by a content management system (“CMS”) operating on, or under the control of, the application server. In one example, a user, through a device operated by the user, might submit a search request for a certain type of item. In this case, the data store might access the user information to verify the identity of the user and can access the catalog detail information to obtain information about items of that type. The information then can be returned to the user, such as in a results listing on a web page that the user is able to view via a browser on the user device 802. Information for a particular item of interest can be viewed in a dedicated page or window of the browser. It should be noted, however, that embodiments of the present disclosure are not necessarily limited to the context of web pages, but may be more generally applicable to processing requests in general, where the requests are not necessarily requests for content.

Each server typically will include an operating system that provides executable program instructions for the general administration and operation of that server and typically will include a computer-readable storage medium (e.g., a hard disk, random access memory, read only memory, etc.) storing instructions that, when executed (i.e., as a result of being executed) by a processor of the server, allow the server to perform its intended functions.

The environment, in one embodiment, is a distributed and/or virtual computing environment utilizing several computer systems and components that are interconnected via communication links, using one or more computer networks or direct connections. However, it will be appreciated by those of ordinary skill in the art that such a system could operate equally well in a system having fewer or a greater number of components than are illustrated in FIG. 8. Thus, the depiction of the system 800 in FIG. 8 should be taken as being illustrative in nature and not limiting to the scope of the disclosure.

The various embodiments further can be implemented in a wide variety of operating environments, which in some cases can include one or more user computers, computing devices or processing devices which can be used to operate any of a number of applications. User or client devices can include any of a number of computers, such as desktop, laptop or tablet computers running a standard operating system, as well as cellular, wireless and handheld devices running mobile software and capable of supporting a number of networking and messaging protocols. Such a system also can include a number of workstations running any of a variety of commercially-available operating systems and other known applications for purposes such as development and database management. These devices also can include other electronic devices, such as dummy terminals, thin-clients, gaming systems and other devices capable of communicating via a network. These devices also can include virtual devices such as virtual machines, hypervisors and other virtual devices capable of communicating via a network.

Various embodiments of the present disclosure utilize at least one network that would be familiar to those skilled in the art for supporting communications using any of a variety of commercially-available protocols, such as Transmission Control Protocol/Internet Protocol (“TCP/IP”), User Datagram Protocol (“UDP”), protocols operating in various layers of the Open System Interconnection (“OSI”) model, File Transfer Protocol (“FTP”), Universal Plug and Play (“UpnP”), Network File System (“NFS”), Common Internet File System (“CIFS”) and AppleTalk. The network can be, for example, a local area network, a wide-area network, a virtual private network, the Internet, an intranet, an extranet, a public switched telephone network, an infrared network, a wireless network, a satellite network, and any combination thereof. In some embodiments, connection-oriented protocols may be used to communicate between network endpoints. Connection-oriented protocols (sometimes called connection-based protocols) are capable of transmitting data in an ordered stream. Connection-oriented protocols can be reliable or unreliable. For example, the TCP protocol is a reliable connection-oriented protocol. Asynchronous Transfer Mode (“ATM”) and Frame Relay are unreliable connection-oriented protocols. Connection-oriented protocols are in contrast to packet-oriented protocols such as UDP that transmit packets without a guaranteed ordering.

In embodiments utilizing a web server, the web server can run any of a variety of server or mid-tier applications, including Hypertext Transfer Protocol (“HTTP”) servers, FTP servers, Common Gateway Interface (“CGI”) servers, data servers, Java servers, Apache servers, and business application servers. The server(s) also may be capable of executing programs or scripts in response to requests from user devices, such as by executing one or more web applications that may be implemented as one or more scripts or programs written in any programming language, such as Java®, C, C# or C++, or any scripting language, such as Ruby, PHP, Perl, Python or TCL, as well as combinations thereof. The server(s) may also include database servers, including without limitation those commercially available from Oracle®, Microsoft®, Sybase and IBM® as well as open-source servers such as MySQL, Postgres, SQLite, MongoDB, and any other server capable of storing, retrieving, and accessing structured or unstructured data. Database servers may include table-based servers, document-based servers, unstructured servers, relational servers, non-relational servers or combinations of these and/or other database servers.

The environment can include a variety of data stores and other memory and storage media as discussed above. These can reside in a variety of locations, such as on a storage medium local to (and/or resident in) one or more of the computers or remote from any or all of the computers across the network. In a particular set of embodiments, the information may reside in a storage-area network (“SAN”) familiar to those skilled in the art. Similarly, any necessary files for performing the functions attributed to the computers, servers or other network devices may be stored locally and/or remotely, as appropriate. Where a system includes computerized devices, each such device can include hardware elements that may be electrically coupled via a bus, the elements including, for example, at least one central processing unit (“CPU” or “processor”), at least one input device (e.g., a mouse, keyboard, controller, touch screen or keypad) and at least one output device (e.g., a display device, printer or speaker). Such a system may also include one or more storage devices, such as disk drives, optical storage devices and solid-state storage devices such as random access memory (“RAM”) or read-only memory (“ROM”), as well as removable media devices, memory cards, flash cards, etc.

Such devices also can include a computer-readable storage media reader, a communications device (e.g., a modem, a network card (wireless or wired), an infrared communication device, etc.), and working memory as described above. The computer-readable storage media reader can be connected with, or configured to receive, a computer-readable storage medium, representing remote, local, fixed, and/or removable storage devices as well as storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information. The system and various devices also typically will include a number of software applications, modules, services or other elements located within at least one working memory device, including an operating system and application programs, such as a client application or web browser. In addition, customized hardware might also be used and/or particular elements might be implemented in hardware, software (including portable software, such as applets) or both. Further, connection to other computing devices such as network input/output devices may be employed.

Storage media and computer readable media for containing code, or portions of code, can include any appropriate media known or used in the art, including storage media and communication media, such as, but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information such as computer readable instructions, data structures, program modules or other data, including RAM, ROM, Electrically Erasable Programmable Read-Only Memory (“EEPROM”), flash memory or other memory technology, Compact Disc Read-Only Memory (“CD-ROM”), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other medium which can be used to store the desired information and which can be accessed by the system device. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will appreciate other ways and/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. It will, however, be evident that various modifications and changes may be made thereunto without departing from the broader spirit and scope of the invention as set forth in the claims.

Other variations are within the spirit of the present disclosure. Thus, while the disclosed techniques are susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific form or forms disclosed, but on the contrary, the intention is to cover all modifications, alternative constructions and equivalents falling within the spirit and scope of the invention, as defined in the appended claims.

The use of the terms “a” and “an” and “the” and similar referents in the context of describing the disclosed embodiments (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. The term “connected,” when unmodified and referring to physical connections, is to be construed as partly or wholly contained within, attached to or joined together, even if there is something intervening. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein and each separate value is incorporated into the specification as if it were individually recited herein. The use of the term “set” (e.g., “a set of items”) or “subset” unless otherwise noted or contradicted by context, is to be construed as a nonempty collection comprising one or more members. Further, unless otherwise noted or contradicted by context, the term “subset” of a corresponding set does not necessarily denote a proper subset of the corresponding set, but the subset and the corresponding set may be equal.

Conjunctive language, such as phrases of the form “at least one of A, B, and C,” or “at least one of A, B and C,” unless specifically stated otherwise or otherwise clearly contradicted by context, is otherwise understood with the context as used in general to present that an item, term, etc., may be either A or B or C, or any nonempty subset of the set of A and B and C. For instance, in the illustrative example of a set having three members, the conjunctive phrases “at least one of A, B, and C” and “at least one of A, B and C” refer to any of the following sets: {A}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B, C}. Thus, such conjunctive language is not generally intended to imply that certain embodiments require at least one of A, at least one of B and at least one of C each to be present.

Operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. Processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions and may be implemented as code (e.g., executable instructions, one or more computer programs or one or more applications) executing collectively on one or more processors, by hardware or combinations thereof. The code may be stored on a computer-readable storage medium, for example, in the form of a computer program comprising a plurality of instructions executable by one or more processors. The computer-readable storage medium may be non-transitory. In some embodiments, the code is stored on set of one or more non-transitory computer-readable storage media having stored thereon executable instructions that, when executed (i.e., as a result of being executed) by one or more processors of a computer system, cause the computer system to perform operations described herein. The set of non-transitory computer-readable storage media may comprise multiple non-transitory computer-readable storage media and one or more of individual non-transitory storage media of the multiple non-transitory computer-readable storage media may lack all of the code while the multiple non-transitory computer-readable storage media collectively store all of the code.

Accordingly, in some examples, computer systems are configured to implement one or more services that singly or collectively perform operations of processes described herein. Such computer systems may, for instance, be configured with applicable hardware and/or software that enable the performance of the operations. Further, computer systems that implement various embodiments of the present disclosure may, in some examples, be single devices and, in other examples, be distributed computer systems comprising multiple devices that operate differently such that the distributed computer system performs the operations described herein and such that a single device may not perform all operations.

The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

Embodiments of this disclosure are described herein, including the best mode known to the inventors for carrying out the invention. Variations of those embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate and the inventors intend for embodiments of the present disclosure to be practiced otherwise than as specifically described herein. Accordingly, the scope of the present disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the scope of the present disclosure unless otherwise indicated herein or otherwise clearly contradicted by context.

All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein. 

What is claimed is:
 1. A computer-implemented method, comprising: processing data to be stored via a plurality of hosts, each host of the plurality of hosts having a plurality of data storage devices, by at least: applying a redundancy code to the data so as to generate a plurality of shards, the plurality of shards having a quorum quantity which is less than a quantity of shards in the plurality of shards, the quorum quantity sufficient to regenerate any other shard of the plurality of shards; and allocating the plurality of shards to respective hosts of the plurality of hosts so as to decorrelate a first failure mode associated with the plurality of shards by decorrelating a first failure event of a first shard of the plurality of shards from a second failure event of a second shard of the plurality of shards; causing each host of the plurality of hosts to randomly select, by a selector, a selected data storage device of the plurality of data storage devices for storage of shards allocated to the host, so as to decorrelate a second failure mode by decorrelating a third failure event of the selected storage device of the plurality of data storage devices from a fourth failure event of a second data storage device of the plurality of data storage devices; and causing storage, on the plurality of hosts, of the plurality of shards on the hosts in accordance with the random selections of the selector.
 2. The computer-implemented method of claim 1, wherein the redundancy code is a linear erasure code.
 3. The computer-implemented method of claim 1, wherein a subset of the plurality of shards includes at least one data shard that includes an original form of the data.
 4. The computer-implemented method of claim 1, further comprising responding to requests for at least a subset of the data by retrieving the subset from a subset of hosts on which the data is stored.
 5. A system, comprising at least one computing device that implements one or more services, wherein the one or more services at least: apply a redundancy code to data to be stored via a plurality of hosts, each host of the plurality of hosts having a plurality of data storage devices, so as to generate a plurality of shards having a quorum quantity of shards, less than a quantity of shards in the plurality of shards, being sufficient to regenerate any other shard of the plurality of shards; cause, by a selector implemented by the one or more services, each host of the plurality of hosts to select a selected data storage device of the plurality of data storage devices for storage of shards allocated to the host, so as to decorrelate a set of related events associated with the plurality of data storage devices such that a respective event of the set of related events affects a smaller subset of the plurality of data storage devices selected for storage of a shard relative to not decorellating the set of related events, each event of the set of related events being associated with failure of one or more data storage devices of the plurality of data storage devices; and store, on the plurality of hosts, the plurality of shards via the hosts on a plurality of respective selected data storage devices.
 6. The system of claim 5, wherein the one or more services is further configured to apply the redundancy code such that an original form of the data is stored to a subset of the plurality of shards.
 7. The system of claim 6, wherein the shards are stored such that a shard of the plurality of shards, the shard comprising original data of a respective subset of the data, is entirely stored within a single data storage device of the plurality of data storage devices.
 8. The system of claim 5, wherein the set of related events is associated with a correlated failure of two or more of the plurality of data storage devices.
 9. The system of claim 5, wherein the set of related events is associated with a failure of a subset of the plurality of hosts.
 10. The system of claim 5, wherein the set of related events is associated with corruption of a subset of the plurality of shards.
 11. The system of claim 5, wherein each shard of the plurality of shards correspond to one data storage device of the plurality of data storage devices.
 12. The system of claim 5, wherein the redundancy code is Reed-Solomon.
 13. A set of one or more non-transitory computer-readable storage media having stored thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to: generate, by a redundancy code, a plurality of shards from received data, the plurality of shards to be stored via a plurality of hosts, each host of the plurality of hosts having a plurality of data storage devices, the plurality of shards having a quorum quantity of shards that is less than a quantity of shards in the plurality of shards, the quorum quantity of shards being sufficient, via application of the redundancy code, to regenerate any other shard of the plurality; select, by a selector implemented by the computer system, for each host of the plurality of hosts, a selected data storage device of the plurality of data storage devices of the host for storage of a subset of the plurality of shards allocated to the host, so as to, in response to a storage failure event capable of occurring to a plural subset of the plurality of data storage devices, increase a first probability that at least a quorum of shards stored across the plurality of shards remains available relative to a second probability of availability of at least a quorum of shards prior to causing the computer system to select the selected data storage device; and store, on the plurality of hosts, the plurality of shards via the hosts on a plurality of respective selected data storage devices.
 14. The non-transitory computer-readable storage medium of claim 13, wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to select the selected data storage device by using a random number generator.
 15. The non-transitory computer-readable storage medium of claim 14, wherein the random number generator is a pseudorandom number generator.
 16. The non-transitory computer-readable storage medium of claim 14, wherein the random number generator uses an entropic source that is not associated with time.
 17. The non-transitory computer-readable storage medium of claim 14, wherein the random number generator uses an entropic source associated with the plurality of data storage devices.
 18. The non-transitory computer-readable storage medium of claim 13, wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to stochastically select the selected data storage device.
 19. The non-transitory computer-readable storage medium of claim 13, wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to deterministically select the selected data storage device.
 20. The non-transitory computer-readable storage medium of claim 13, wherein the selector is a physical device associated with the host. 